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Weight-Bearing Estimation for Cane Users by Using Onboard Sensors

Division of Intelligent Future Technologies, Mälardalen University, 721 23 Västerås, Sweden
Department of Electronic Technology, University of Malaga, 29071 Malaga, Spain
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2019, 19(3), 509;
Received: 5 December 2018 / Revised: 14 January 2019 / Accepted: 22 January 2019 / Published: 26 January 2019
(This article belongs to the Special Issue Sensors for Gait, Posture, and Health Monitoring)
Mobility is a fundamental requirement for a healthy, active lifestyle. Gait analysis is widely acknowledged as a clinically useful tool for identifying problems with mobility, as identifying abnormalities within the gait profile is essential to correct them via training, drugs, or surgical intervention. However, continuous gait analysis is difficult to achieve due to technical limitations, namely the need for specific hardware and constraints on time and test environment to acquire reliable data. Wearables may provide a solution if users carry them most of the time they are walking. We propose to add sensors to walking canes to assess user’s mobility. Canes are frequently used by people who cannot completely support their own weight due to pain or balance issues. Furthermore, in absence of neurological disorders, the load on the cane is correlated with the user condition. Sensorized canes already exist, but often rely on expensive sensors and major device modifications are required. Thus, the number of potential users is severely limited. In this work, we propose an affordable module for load monitoring so that it can be widely used as a screening tool. The main advantages of our module are: (i) it can be deployed in any standard cane with minimal changes that do not affect ergonomics; (ii) it can be used every day, anywhere for long-term monitoring. We have validated our prototype with 10 different elderly volunteers that required a cane to walk, either for balance or partial weight bearing. Volunteers were asked to complete a 10 m test and, then, to move freely for an extra minute. The load peaks on the cane, corresponding to maximum support instants during the gait cycle, were measured while they moved. For validation, we calculated their gait speed using a chronometer during the 10 m test, as it is reportedly related to their condition. The correlation between speed (condition) and load results proves that our module provides meaningful information for screening. In conclusion, our module monitors support in a continuous, unsupervised, nonintrusive way during users’ daily routines, plus only mechanical adjustment (cane height) is needed to change from one user to another. View Full-Text
Keywords: smart cane; weight-bearing; gait analysis; health monitoring smart cane; weight-bearing; gait analysis; health monitoring
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MDPI and ACS Style

Ballesteros, J.; Tudela, A.; Caro-Romero, J.R.; Urdiales, C. Weight-Bearing Estimation for Cane Users by Using Onboard Sensors. Sensors 2019, 19, 509.

AMA Style

Ballesteros J, Tudela A, Caro-Romero JR, Urdiales C. Weight-Bearing Estimation for Cane Users by Using Onboard Sensors. Sensors. 2019; 19(3):509.

Chicago/Turabian Style

Ballesteros, Joaquin, Alberto Tudela, Juan R. Caro-Romero, and Cristina Urdiales. 2019. "Weight-Bearing Estimation for Cane Users by Using Onboard Sensors" Sensors 19, no. 3: 509.

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